Understanding Suicide over the Life Course Using Data Science Tools within a Triangulation Framework-Journal of Psychiatry and Brain Science-CSCIED科技核心评价数据库-手机版

Understanding Suicide over the Life Course Using Data Science Tools within a Triangulation Framework

Understanding Suicide over the Life Course Using Data Science Tools within a Triangulation Framework

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DOI	10.20900/jpbs.20230003
刊名	Journal of Psychiatry and Brain Science JPBS
年，卷(期)	2023, 8(1)
作者	Lily Johns,Chuwen Zhong,Briana Mezuk*,
作者单位	Center for Social Epidemiology and Population Health, Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA
Abstract	Suicide and suicidal behaviors are important global health concerns. Preventing suicide requires a nuanced understanding of the nature of suicide risk, both acutely during periods of crisis and broader variation over the lifespan. However, current knowledge of the sources of variation in suicide risk is limited due to methodological and conceptual challenges. New methodological approaches are needed to close the gap between research and clinical practice. This review describes the life course framework as a conceptual model for organizing the scientific study of suicide risk across in four major domains: social relationships, health, housing, and employment. In addition, this review discusses the utility of data science tools as a means of identifying novel, modifiable risk factors for suicide, and triangulation as an overarching approach to ensuring rigor in suicide research as means of addressing existing knowledge gaps and strengthening future research.
KeyWord	suicide; suicide prevention; life course framework; data science; triangulation
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Lily Johns,Chuwen Zhong,Briana Mezuk*. Understanding Suicide over the Life Course Using Data Science Tools within a Triangulation Framework, Journal of Psychiatry and Brain Science. 2023; 8; (1). https://doi.org/10.20900/jpbs.20230003.

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